title: "RAG vs. ajustement fin d’un LLM : trouver la solution la mieux adaptée aux entreprises"

Businesses can enhance Large Language Models (LLMs) for specific needs using two main methods: Retrieval-Augmented Generation (RAG) and fine-tuning. The primary goal is to create more precise and personalized AI solutions that are perfectly tailored for unique enterprise use cases. Interestingly, these two approaches can also be combined to achieve even more accurate and customized results. This hybrid strategy allows for an AI that is both knowledgeable about specific data and adapted to a particular style or task.